ResearchReport_LibraryEskills

Readiness of Library Users for a Smart City: A Study of
Self-Perceived e-Skills versus Actual e-Skills
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Research Report 
Yaseen Patel 
Student number: 552925 
Cell: (+27) 76 585 0414
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Supervisor:  
Jason Cohen
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Information Systems Division
August 2015
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Table of Contents
TABLE OF CONTENTS 2........................................................................................
CHAPTER 1 - INTRODUCTION 5..............................................................................
1. Introduction 5..........................................................................................
2. Purpose of the study 6............................................................................
3. Context and Background 6......................................................................
4. Research Problem 10..............................................................................
i. Purpose of the Study 10...............................................................
ii. Sub-Problems 10...........................................................................
5. Objectives of the Study 11.......................................................................
1.7 Importance of the Study 11...............................................................................
i. Research Gap 11.....................................................................................
ii. Contribution to Practice 12...........
6. Delimitations of the Study 13...................................................................
1.9 Research Report Outline 13.............................................................................
Chapter 2 – Literature Review 13.......................................................................
Chapter 3 – Research Methodology 13..............................................................
Chapter 4 – Empirical Results 14........................................................................
Chapter 5 - Discussion and Implications 14........................................................
Chapter 6 – Conclusion 14..................................................................................
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CHAPTER 2 – LITERATURE REVIEW 14..................................................................
1. Introduction 14..............................................................................................
2. Self-perceived E-skills 16..........................................................................
2.1. Computer Self-Efficacy 16.............................................................
3. Actual E-Skills 21.......................................................................................
4. Observed E-Skills vs Self-Perceived E-Skills 25........................................
5. Conceptual Model 28..................................................................................
5.1. Hypotheses: 28..............................................................................
CHAPTER 3 – RESEARCH METHODOLOGY 30.........................................................
3.1 Introduction 30..................................................................................................
3.1.1 Research methodology / paradigm 30.......................................................
3.1.2 Research Design 31...................................................................................
3.2 Population and sample 32................................................................................
3.2.1 Population 32.............................................................................................
3.2.2 Sample and sampling method 32...............................................................
3. The Research Instrument 36........................................................................
4. Procedure for Data Collection 40..................................................................
5. Data Analysis and Interpretation 43...............................................................
6. Limitations 44...............................................................................................
7. Validity and Reliability 44..............................................................................
8. Ethics 45
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9. Research planning 46........................................................................................
CHAPTER 4 46.....................................................................................................
Descriptive Statistics 47..........................................................................................
Data Screening, Missing Values and Outliers 47................................................
Respondent Profile 48.........................................................................................
Hypotheses Testing 56...........................................................................................
CHAPTER 5 66.....................................................................................................
CHAPTER 6 69.....................................................................................................
Purpose 69.............................................................................................................
Results 69...............................................................................................................
Limitations 69..........................................................................................................
Future Research 70................................................................................................
Conclusion 70.........................................................................................................
REFERENCES 72.................................................................................................
3.11 APPENDIX 75................................................................................................
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CHAPTER 1 - INTRODUCTION
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1. Introduction
E-skills refers to a wide-ranging skill set that is essential in today’s digital
economic environment (ENTR.E.4, 2014). Therefore, with reference to users of
Information and Communication Technology (ICT), e-skills are defined by the
abilities mandatory for the current use of ICT systems and devices by the
individual (Lawal, 2005). User skills cover the use of common software tools and
of specialized tools supporting which is necessary for functions in order to
complete specific tasks. E-skills at the general level cover "digital literacy"
which is the skills obligatory for the confident and critical use of ICT for leisure,
work, communication and learning (Hargittai & Hsieh, 2012). The e-skills of
residents are important to the success of smart city initiatives. However, smart
city planners often lack reliable tools to assess the readiness and skills of city
residents for new ICT implementations, and instead may choose to rely on self-
perceptions. This is problematic as individuals may over-estimate their e-skills,
which may put implementation efforts at risk. Furthermore, this may cause
opportunities to intervene such as training programmes to be missed.
The research presented aims to examine the question of whether self-reported
e-skills can be a reliable indication of actual e-skills, and therefore valid not
just for empirical research but also to inform smart city planners. The purpose
of this study was to investigate e-skills of library users’ in the City of
Johannesburg (CoJ) for using the new ICTs provided by city libraries.
Additionally, self-perceived e-skills will also be assessed. This research report is
to use the quantitative methodology, descriptive research method undertaking a
positivist paradigm. In order to participate in this study, the city residents will
have to make use of CoJ public libraries. These libraries are a part of the
2014/2015 Implementation Plan know more commonly as the Public Access to
Internet in Libraries project (PAIL) with the objective to proactively engage with
community development. Member of the Mayoral Committee (MMC) for
Corporate and Shared Services Councillor, Mally Mokoena, explained that even
though the intended target audience is all residents of the City, a deeper focus
is placed on the youth and school going children.
This introductory section aims to focus on describing the research problem and
context, presenting the research objectives and its importance/significance.
However, the starting point for most research is highlighting the purpose of the
study.
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2. Purpose of the study
The goal of this specific study is to study the reliability of self-reported e-skills
of CoJ library users.
This goal is to be achieved by evaluating the readiness of residents regarding ICT
infrastructure upgrades within CoJ public libraries, in the efforts towards
creating a smart city.
The smart city initiative entails a long term process which may require the city
to adapt to new challenges therefore risk failure if the intended users do not
embrace the changes. This research determines the readiness through
empirically assessing the e-skills of library users in a quantitative study, which
will subsequently be compared to their level of computer self-efficacy as well as
self-reported e-skills. The study used a two-phase data gathering approach to
compare self-reported e-skills to an objective measure of e-skills. This will
provide insight on the residents’ e-skills as a determining factor to the
utilization of ICT upgrades as well as to the accomplishment of current or future
smart city initiatives.
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3. Context and Background
This research is to contribute to the overarching project: Information Systems
for Smart Cities in Africa. The project involves the University of the
Witwatersrand , the City of Johannesburg and is funded by the National1 2
Research Foundation of South Africa .3
It has been a recent trend for governments around the world to turn their cities
into ‘smart cities’(Allwinkle and Cruickshank, 2011). A major objective for this
goal involves the implementation of ICTs into city structures (Hollands,
2008;Neirotti et al., 2014). In the framework of this study, the City of
Johannesburg has adopted Caragliu et al.’s (2011) definition of a smart city as
one which utilizes ICTs effectively in order to invest in social capital, human
capital and modern communication infrastructure. These aspects are ideally
coupled with efficient disposal of resources through elaborate governance to
directly result in both supportable economic growth and increased value of life
for residents.
The notion of a smart city has been relatively popular in the global context
during current years hence the definitions discovered thus far has been often
criticized as abstract (Caragliu et al., 2011; Hollands, 2008). The smart city
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Website: http://www.wits.ac.za/1
Website: http://www.joburg.org.za/2
Website: http://www,nrf.ac.za/3

concept was developed with the intention to provide improved living conditions
by providing smart solutions to common issues faced by the city stakeholders
(Giovannella et. al, 2013). The general view behind existing definitions implies
that notion of a smart city encompasses aspects of “organisational change,
technological advancement, economic, social development and other dynamics
of a modern city” (e.g. Neirotti et al., 2014; Caragliu, Del Bo and Nijkamp,
2011; Odendaal, 2003; Giffinger and Pichler-Milnovic, 2007; Central Strategy
Unit, Office of the Executive Mayor, 2011). Africa has fallen behind compared to
Western countries considering smart city transformation. African cities are
attempting to redeem a smart city status by implementing smart city strategies
relevant to each city’s context (Odendaal, 2006). In operationalising this,
projects are underway to address digitally connected living as the prerequisite
to informated living (Odendaal, 2006).
In the past, research on smart cities in Africa has indicated that areas of
application that are implemented are constrained on factors including the
economic development, structural urban variables such as geographic location,
and population density (Neirotti et al., 2014). The focus of most African
governments’ smart city efforts is on ICT infrastructure aimed to firstly guide
digitally connected living, followed by a focus on service delivery (Chanyagorn &
Kungwannarongkun, 2011). ICT infrastructure is seen as necessary to deliver
services and to create equity of access for residents (Chanyagorn &
Kungwannarongkun, 2011a). Services that are identified as priorities relate to
local conditions. Hollands (2008) makes it clear that the “definitional
impreciseness” of smart cities covers a range of assumptions about cities, their
functions and the roles of people within them (Vijayakumar & Kannappanavar,
2012). Where cities focus is on economic growth, a risk emerges of further
dividing the population by economic status or IT skills (Lawal 2005).
South African cities that are on course with smart city strategies include
Durban, Cape Town and the City of Johannesburg (Odendaal, 2006). Durban has
formulated an extensive expansion plan which has been separated into minor,
five year draft Integrated Development Plans (IDP’s) that will lead the growth of
the eThekwini Metropolitan Municipality so that all services are delivered in a
synergised manner, taking into consideration all parts of residents’ lives
(Ballantine et al., 2007). In The City of Cape Town the five focus areas in
regards to a smart City is ‘the opportunity city, the safe city, the caring city, the
inclusive city and the well-run city’ which all imply relatedness to smart city
dimensions (Ballantine et al., 2007).
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The City of Johannesburg (COJ) is a metropolitan municipality serving South
African communities needs in the region of Gauteng (City of Johannesburg,
2013). The provincial population consist of over seven million individuals (City of
Johannesburg, 2013). The City of Johannesburg still faces many challenges
which could limit the adoption such as those caused by the digital divide. Digital
divide is known as the gap between demographics and regions that have access
to modern information and communications technology, and those that do not or
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have restricted access. This technology can include television, telephone,
internet and personal computers (City of Johannesburg, 2013).
According to Nobunto Mpendulo, Director of CoJ Library and Information
Services, The CoJ Library and Information services acknowledged their duty to
make information easily available in electronic formats. In the year 2005, the
City implemented a programme to arrange for free right to use the electronic
information through libraries. The following year in each library in the city both
the Library and Information Services and the Office of the CIO began to launch
internet workshops, an estimated 900 workshops in 85 libraries (Central Strategy
Unit, Office of the Executive Mayor, 2011).The creation of multi-purpose
Community Centres supports the e-Government initiative (Alomari et al. 2009).
Libraries will become the access points, for all obtainable internet information
such as information provision, social networking and community engagement to
support the city’s social inclusion and poverty abolition strategies as well as
empowering the poor to access basic livelihoods which will helping them to
access information on grants given by government, encouraging skills
development and accessibility to basic employment opportunities that may arise
(Central Strategy Unit, Office of the Executive Mayor ,2011). The benefits for
the user include free internet access to and open source productivity software
in a controlled and safe environment. There is also support and guidance
available for school going kids. The support done includes guiding in terms of
homework and project resources, last of all a platform to engage with local
government, showcase community projects and undertake entrepreneurial
initiatives as mentioned above in regards to grants and so forth (Gross &
Latham, 2007)
The CoJ produced a short term integration plan (2013) intended to be
implemented by the year 2016 which obligates itself to hands on delivery of a
better city environment (City of Johannesburg, 2012; City of Johannesburg,
2015). Its objectives are to achieve this through long-term plans, targeted
programs, services and enabling support that drives economic growth (Setapa et
al., 2012)
Libraries can be found across the city’s seven regions. A term of office
deliverable by 2016 includes PAIL is at all libraries with the desired outcome by
2020 to be identified with a strategic emphasis on learning and literacy. The
CoJ public libraries, which are based around the city, have recently been
upgraded including the ICT infrastructure. It now has public access computers
and Wi-Fi areas, but it does not help having access to these technologies when
individuals are unable to use them effectively; an important element of digitally
connected living is having e-skills to be able to use such technologies.
In order to comprehend the importance of the smart city concept, it is vital to
clearly define ICT. ICT is technologies that provide access to information through
telecommunications (Chanyagorn & Kungwannarongkun, 2011b). Since ICT is a
subset of Information Technology (IT), the focus in primarily on communication
technologies. This includes the internet, wireless networks, tablets, and other
communication mediums. The value of modern ICTs has recognised the creation
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of a “global village”, in which communication is both more efficient and
effective. Technology is a vital factor that has many influences in smart city
definitions. Depending on the circumstances, technology could facilitate better
operations (automating) of city services (Backhouse & Cohen, 2014). Another
instance where technology could play a role is to develop, grow or manage
cities in an ecologically responsible or sustainable manner (Backhouse & Cohen,
2014). Lastly, we should be aware that information technology provides the
opportunity to produce informative aspects to city services by connected living
(Backhouse & Cohen, 2014).
As of today, ICTs’ role in tackling problems faced by cities with more
environmentally friendly and economically viable solutions (Kondepudi et al.
2014). The International Telecommunication Union (ITU) globally prioritizes ICT
for development in a nation (Olugbara et al., 2014). A common belief of
developed nations is that “technology is the reason for the unsurpassed levels of
affluence” (Olugbara et al., 2014). social and professional opportunities were
once based on the ability to be literate and the ability to develop and work with
the new technologies of the computer and internet, which currently provides
similar opportunities in our current day and age (Vijayakumar & Kannappanavar,
2012). ICT is evident to be a key productive force in the socioeconomic
development of rural and urban societies as the internet, broadband and cloud
technologies offer benefits that include rising the standards of living, increasing
levels of literacy, increasing access to data, enabling and accelerating
development and increasing the participation in the global knowledge economy
(Olugbara et al., 2014). This renews the importance of upgrading technology
infrastructures at a local level. However, these upgrades must be coupled with
the appropriate skills possessed by residents to be considered a success.
On 30 September 2011 at Turbine Hall in Newtown the outreach programme
event took place, which focused on smart cities. The acting chief information
officer in the City of Johannesburg, Abraham Mahlangu said, “Technology alone
won’t make the City of Johannesburg a smart city, although it is a mighty
enabler.” Poverty, unemployment, and inequality facing humanity has been a
huge social challenge. Literature shows that computer skills, which inevitably
include e-skills, are prominent factors to deal with the above mentioned social
challenges (Caragliu et al., 2011). The skills required to make use of ICTs are
referred to as “e-skills”. A broad range and depth of e-skills exists as ICT is
commonly used in a multitude of environments or purposes. The terms
computer literacy, or digital literacy, are commonly understood to relate to this
concept (Lawal, 2005)
"E-skills" contain a wide-range of skills essential in the modern workplace and
digital economy. ICT involves “cross-disciplinary, cognitive and problem-solving
skills” in addition to a comprehending the basics of business and communication
skills, including understanding of foreign languages. These have to be
understood as the core set of capabilities preparing all citizens for a knowledge-
based society. These key capabilities should be provided in a lifelong knowledge
context (Anon n.d.).
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In South African context, e-skills correspondingly is defined by set of skills to use
ICT within a “developing information society and the global knowledge
economy” in which ICT has become an indispensable requirement for
advancement in government, business, education and society at large (Khan,
Moon, Rhee, & Rho, 2010). This study lends the definition of ICT User skills as
those which are needed to successfully and productively interact with ICT’s
provided in a smart city. Other common definitions and assessments comprise of
skillsets which include standard program skills, application skills such as word
processors and internet skills (Odendaal, 2006).
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4. Research Problem
Self-reported e-skills have proved to be high from previous surveys (in parts of
Johannesburg), but the extent of reliability is not clear (Cohen & Backhouse,
2015). The readiness for a smart city is still uncertain. It is arguable that the
lack of evidence on e-skills and the extent to which self-perceptions is a reliable
indicator is questionable. ICT upgrades in public government service facilities
addresses the issue of access, but another aspect of a smart city is
participation. The success of smart city initiatives depends on the residents
abilities to make use of the technologies (Ballantine et al., 2007). Without
properly understanding e-skills and intervening where appropriate then
initiatives may fail. Therefore the study will be examining constructs of
resident’s computer self-efficacy, their performance expectancy, and actual
performance. The extent to which self-reports can be used to predict actual
performance will be determined.
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i. Purpose of the Study
The purpose of this research study is to examine the level of reliability of the
self-perceived e-skills of city library users through an empirical cross-sectional
survey; to determine the correlation between their subjective, self-perceptions
of e-skills and objectively determined e-skills; and to determine if city library
users possess the adequate e-skills to effectively utilize the upgraded ICT
infrastructure offered by city libraries.
This paper will have particular focus on basic internet skills as the determinant
of e- skills.
ii. Sub-Problems
The first sub-problem is to assess the e-skills of library users. This will be
achieved by examining the extent to which participants can complete given
tasks on a tablet device and the time taken to complete those tasks.
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The second sub-problem is to determine the extent of which participants’ actual
e-skills correlate with their computer self-efficacy and their self-reported
performance expectancies on the various tasks. Thus, the aim of this research is
to identify if the level of computer self-efficacy together with self-reported e-
skills correlate with library users’ actual e-skills. Additionally, an aim of this
research is to contribute to the existing body of knowledge about computer self-
efficacy and self-reported e-skills related to actual e-skills.
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5. Objectives of the Study
The following are the objectives of this study:
1. To read literature on computer self-efficacy, self-reported e-skills, and e-skills assessments
2. To develop a model to explain the study
3. To identify the population sample and method
4. To draw up a survey related to the topics read in literature
5. To hand out the survey to the target sample
6. To analyse and interpret the data
7. To report on the findings of the study
8. To identify the limitations of the study and future recommendations
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1.7 Importance of the Study
The significance of this study might suggest that e-skills may be important to
utilization and success of smart city initiatives such as the PAIL project of the
COJ.
This is to make a valuable contribution to the field of information systems in
terms of both research and practice.
i. Research Gap
The study fills a research gap by determining if self-reported e-skills within the
context of CoJ libraries is reliable as a construct that is often an independent
variable for information systems research (Merritt et al., 2005). Enhancing the
study is that the computer self-efficacy (CSE) construct in research is measured
in parallel with the construct of performance expectancy thus intended to
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capture the self-perceptions of ICT abilities in general as well as for specific
tasks.
This study will additionally explore the research gap by suggesting the level of
appropriateness of common measures to assessing levels of e-skills, due to the
extent of reliability of an individual’s self-reported e-skills are evaluated by
comparing those self-reports with objective measures.
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ii. Contribution to Practice
Research has been completed in recent years on e-skills of information
professionals in developing countries (Lawal, 2005). Past research also often
placed emphasis on the perceived benefits and importance of ICTs as well as
users experience in computer usage and training (Vijayakumar &
Kannappanavar, 2012). Research has yet to be extensively covered in: the
assessment of self-reported e-skills of library users in the Johannesburg context;
this study will also address the level of basic computer skills which is relevant to
ICT usage to e-governance as well as offer suggested methods to attain accurate
self-reports in perspective of a South African environment.
By uncovering the ability of residents through a basic e-skills test, this study will
offer assistance to the city when exploring additional smart city initiatives as it
relates to the South African context. More specifically, the research could be
replicated in other parts of Johannesburg or various city organisations to
compare levels of reliability of self-reported e-skills. The CSE determines how
confident are residents to learn and engage with later technologies. This will
inform smart city planners about areas that have higher chances of successful
ICT infrastructure implementations; in contrast, areas where low levels of e-
skills are evident, interventions such as training programmes should be
investigated. MMC for Community Development Councillor, Chris Vondo said 40
interns would undergo intensive information technology and entrepreneurial
training in an attempt to further accelerate the City’s Smart City and Smart
Citizen programs. The programme will be run in partnership with the Gauteng
Enterprise Propeller. A further 3 000 digital ambassadors from micro enterprises
would be trained to provide literacy training to communities as required.
MMC Mokoena said the rollout of e-World and the e-learning initiative would
expand the “techno-literacy skills of communities, resulting in empowerment
through the provision of access to online information resources by all sectors of
the community, enabling ordinary people to participate in the global knowledge
economy.” He explained that the programme rollout was significant because it
was a significant aspect of human and social development designed to reveal
potential.
The study will provide guidance to the city in their pursuit of transforming
Johannesburg into a smart city by focusing efforts towards understanding ICT
user attitudes and abilities. It will help city libraries based in Johannesburg to
gain a greater affinity to improved technology infrastructure based on accurate
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user research. This can then inform the health sector for example on how to
achieve desired results of implementing ICT in that sector.
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6. Delimitations of the Study
The study is delimited as follows:
• Participants will be users of CoJ public libraries
• Perceptions of e-skills and computer self-efficacy will be looked at in this
study
• Actual e-skills assessment will include only tasks relevant to e-governance
requisite of a smart city.
• The actual e-skills assessment will not be extensive due to time
constraints per survey
The research topic may focus specifically on city libraries, as time constraints
allow. The 35 libraries that a part of the 2014/2015 Implementation Plan will be
considered in the sampling strategy of this study. In addition, if setting is to
change, only public organisations can be considered. The focus is to be on the
residents who use the library as an accessible facility, and not a place of
employment thus this study excludes library staff. Delimitation includes
interviewing participants and these unstructured methods are time consuming
and part of qualitative methodology.
1.9 Research Report Outline
Chapter 2 – Literature Review
A literature review will be conducted to identify the appropriate model and theories to use in this
study. A literature review on computer self-efficacy, perceived e-skills and actual e-skills
assessments will be conducted. Literature that identifies the relationship between demographic
data and the validity of self-reported e-skills will also be conducted.
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Chapter 3 – Research Methodology
This chapter will cover the research methodology. The population target will be visitors of
Johannesburg city libraries. A quantitative study will be conducted in the form of surveys and
actual assessments. Methods for data analysis and interpretation will be discussed.
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Chapter 4 – Empirical Results
This chapter will be discussing the results from the survey and assessment. It will also look at how
the results relate to the hypotheses proposed in the model. Results from the reliability and validity
test will also be included.
Chapter 5 - Discussion and Implications
This chapter will be discussing the results of the survey and the implications on the research
question and existing knowledge on accuracy of self-reported e-skills.
Chapter 6 – Conclusion
This chapter includes the conclusion, findings and limitations of the study, as well as future
recommendations for studies similar to this.
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Chapter 2 – Literature Review
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1. Introduction
Working Definitions of a Smart City , “ this is a city well performing in a
forward-looking way in terms of mobility, environment, living, people,
governance and economy, built on the smart combination of endowments and
activities of self-decisive, independent and mindful citizens” (Backhouse &
Cohen, 2014; Hollands, 2008). Another, a city “connecting the physical
infrastructure, the IT infrastructure, the social infrastructure, and the business
infrastructure to leverage the collective intelligence of the city” (Carli et al.,
2013). Alternatively, “The use of Smart Computing technologies to make the
critical infrastructure components and services of a city which include city
administration, education, healthcare, public safety, real estate,
transportation, and utilities which are more intelligent, interconnected, and
efficient” (Caragliu et al., 2011).
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Smart city initiatives are a contributing factor to ICTs (Hollands, R.G., 2008). A
number of possible opportunities arise when there is a combination of ICT with
development projects that alter the urban landscape of a city and can improve
the management and functioning of a city (Odendaal, 2006). Based on the
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above evidence , ICT (information and communications technology or
technologies) is a term that includes any communication device or application,
encompassing: computers, cellular phones, network hardware and software,
satellite systems as well as the various services and applications (Chanyagorn &
Kungwannarongkun, 2011b).
In making an effort to understand what is smart about the smart city, one finds
that not only does it include a diverse range of equipment like information
technology, business innovation, governance, communities and sustainability
(Hollands, 2008). It can also be recommended that the label itself often makes
certain conventions about the relationship between these specific equipment’s
(Hollands, 2008). The point here is not to try and offer a better definition
instead, the emphasis of the next section is to critically focus on how ready are
users for a smart city and are their perceived e-skills true to their actual e-skills
(Hollands 2008).
The purpose of this section is to examine the literature review on e-skills and to
propose a conceptual model of the reliability of determinant which affects
actual e-skills.
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E-skills
E-skills are defined as, “The set of skills, knowledge, and concepts that are
needed for effective usage on computers in terms of: location of applications;
operations; management; understanding, and evaluating usage of services
provided in different areas of a computer” (Olugbara et al., 2014). These
include word skills, spreadsheet application skills, presentation software skills,
programming, installing software, internet skills, connecting hardware and many
other capabilities that an individual could use for the advancement technology
usage.
This study classifies that the definition e-skills is skills which are needed to
successfully and productively interact with ICT’s provided in a smart city.
Common definitions and assessments comprise of skill sets which include
standard program skills, application skills such as word processors and internet
skills.
In South African context, e-skills means the set of skills to use ICT within an
emerging information society and the global knowledge economy in which ICT
has become an essential requirement for advancement in businesses, education
and society in general (Khan, Moon, Rhee, & Rho, 2010). It is evident in
literature that computer skills, which predictably include e-skills, are noticeable
factors to deal with social challenges such as poverty, unemployment and
inequality facing humanity (Khan, Moon, Rhee, & Rho, 2010).
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In most studies, self-perceptions are often identifying and examined such as
computer self-efficacy and performance expectancy.
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2. Self-perceived E-skills
2.1. Computer Self-Efficacy
The judgment of one's capability to use a computer is known as Computer self-
efficacy (CSE). It is concerned with what one has done in the past regarding the
usage of computers (Compeau & Higgins, 1995). CSE is defined as an individual’s
judgment of their capability to use a computer (Compeau & Higgins, 1995), and
is a practical indicator of e-skills (Bunz et al., 2007).
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i. CSE
The notion of computer self-efficacy (CSE) has been recently suggested as
important to the study of an individual’s computing behaviour. Self-efficacy
(CSE) has a positive correlation with individual’s readiness to choose and
participate in computer-related activities (Compeau &Higgins, 1995).
This paper extends current knowledge about the concept of self-efficacy in the
context of e-skills performance. Two broad types of self-perceptions, general
CSE and Performance Expectancy, are measured across various computer-related
tasks by proposing that general CSE beliefs will be a strong predictor of the
following Performance Expectancy measure.
The concept of self-efficacy owes much of its theoretical development and
empirical modification to more than two decades of research by Bandura and his
colleagues (Agarwal et al., 2000). Bandura suggests that self-efficacy beliefs are
developed through four primary sources of information: "enactive that serve as
in mastery experiences dictators of capability; vicarious experiences that alter
efficacy beliefs through transmission of competencies and comparisons with the
attainments of others; verbal persuasion and allied types of social influence that
one certain and possesses capabilities; physiological affective states from which
people judge their capability, strength, and vulnerability to
dysfunction" (Bandura, 1997, p. 79).
Efficacy is a behavioural construct which refers to the self-confidence of one’s
capability to create a desired result (Merriam-Webster, 2014). The notion of
efficacy is the basis to many motivational theories (Bandura, 1998, 1990, 1982).
Self-efficacy is evident in numerous forms such as performance and behaviour
which are inclined by one’s motivations (Bandura, 1977). Self-efficacy is defined
by Bandura (1977) as “personal belief concerning ones capabilities to organise
and execute courses of action required to produce given attainments” (Samara
& Raven, 2014).
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It is also important when defining self-efficacy to consider the relevant
dimensions of self-efficacy judgments. Self-efficacy judgments vary on three
distinct but consistent, dimensions: “magnitude”, “strength”, and
“generalizability”(Compeau & Higgins, 1995). The magnitude of self-efficacy
refers to how difficult specific task is. Individuals with a high magnitude of self-
efficacy will see themselves as able to accomplish difficult tasks, while those
with a low self-efficacy magnitude will see themselves as only able to
accomplish simple forms of the behaviour (Compeau & Higgins, 1995).
Individuals who perceive themselves capable of performing certain tasks or
activities are defined as high in self-efficacy and are more likely to try and
execute these tasks and activities. People who perceive themselves as less
capable are less likely to attempt and execute the same given tasks and
activities, and are therefore defined as lower in self-efficacy (Barling & Beattie,
1983).
Since the mid-1970’s, MIS research have been orientated towards understanding
the factors that determine an individual’s use of information technology due to
observing low adoption rates of new technology (Lucas, 1975,1978; Barbeite &
Weiss, 2004a). In order to understand the cognitive state on outcomes of users
towards ICT, self-efficacy theory (Bandura, 1986, 1982) considers perceptions of
future outcomes in order to describe ones interactions and emotions towards
Information Technology. Adopted from Litt (2013), the following studies were
identified:
!
Performance Expectancy
The specific CSE is referred to as Performance Expectancy. Performance
expectancy required the respondent to self-report the performance they
expected on the specific tasks as a predictive measure of the e-skills assessment
outcome. The results from the CSE survey and performance expectations will
provide insight on perceived e-skills.
The degree to which an individual believes that using the system will help him
or her to attain gains in job performance is known as performance expectancy
(Venkatesh et al., 2003). Expectancy is defined as the subjective probability of
effort leading to a specific outcome (Vroom, 1964). In this context, we
hypothesize expectancy as the applicant's belief that trying to do well on a
selection test will lead to a high score on that test (Sanchez et al., 2000).
The responses to the survey items about test-taking motivation could be
affected by respondents' perceptions of test performance. Rudolph J. Sanchez
research paper in his results it indicated that expectancy was related to actual
test performance, and perceived test performance accounted for difference in
post-test reports of motivation after controlling for pre-test levels of
motivation.
Using a five-point scale (not at all skilled, not very skilled, fairly skilled, very
skilled, expert) in Hargittai (2008) users were asked to answer the following
!17

question measured “In terms of your Internet skills, do you consider yourself to
be . . . . ” (“On a scale of 1 to 5”). In Dr. Kimberly Merritt (2005) research paper
the data analysis determined that performance expectancy is not reliable.
The table below indicates previous studies which measure self-perception of e-
skills (self-efficiency and performance expectancy).
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!
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!
!
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Performance Expectancy Survey Measures
Source Assessment detail Example item(s)
Bunz (2004,
2009)
“The computer-email- web
(CEW) fluency scale
measures computers, email,
and internet skills using
seven items”
“I can use the ‘reply’ and ‘forward’
features for email”. “I can create a
website”.
Response items: “Very well”, “well”, “not
so well”, “not at all” (2004: 488).”
Page and
Uncles (2004)
“Questions measure mutual
declarative, mutual
procedural, specialized
declarative, and specialized
procedural web content
information”
“Common declarative web knowledge
example: “The length of time it takes a
page to appear on the screen”. Response
items: “(a) depends on the speed of your
modem-server connection; (b) is
aggravated by pages with lots of pictures;
(c) is associated with the term bandwidth;
(d) all of the above; (e) don’t
know” (2004: 589).”
Spitzberg
(2006)
“Assessment testing the
computer-mediated
communication competence
model”
““I am very familiar with how to
communicate through email and the
internet”.
“I am skilled at timing when I send my
responses to people who email me”.
Response items: “Not at all true of me”,
“mostly not true of me”, “neither true nor
untrue of me/ undecided”, “mostly true of
me”, “very true of me””
!18

!
!
!
Potosky
(2007)
“Internet knowledge
(iKnow) measure assesses
declarative knowledge
and self-rated ability for
online activities”
““I know what a browser is”. Response
items: “I don’t understand this statement
and cannot respond”, “strongly
disagree”, “disagree”, “neither agree nor
disagree”, “agree”, “strongly
agree” (2007: 2768–2769).”
Livingstone
and Helsper
(2007, 2010)
““A single skills scale was
created which summed
the internet-related skills
that each respondent
claimed to be good at
(scale 0–7)” (2007: 693)”
“Sample activities that respondents
claimed to be skilled included: “sending
an instant message”, “downloading and
saving an MP3 [music] file” (2010:
315–316).”
Zimic (2009) “Internet scale composed
of five items; higher totals
indicate higher skill
levels”
“Do you know how to use the following
things on the internet? Send an email?
Attach documents to your email?
Download music? Make a voice-call
online? Set up a server?” Response items:
“Yes”, “No” (2009: 134)”
Jones et al.
(2010)
“9 internet/computer
confidence items”
“Students were asked to report on their
confidence (defined in relation to skill
level) in using various computer
technologies and applications’ such as
‘Writing and commenting on blogs and
Wikis’ and “Online library resources”.
Response items: One (“Not confident/
minimal skill”) through five (“Very
confident/excellent skill level”) (2010:
726).”
Sonck et al.
(2011)
“An instrument with u
items measuring
instrumental and
informational skills”
“Which of these things do you know how
to do on the internet?” Sample items:
“Compare different websites to decide if
information is true” and “Delete the
record of which sites you have visited”.
Response items: “Yes”, “No”, “Don’t
know” (2011: 2).”
(Litt, 2013)
!19

!
3. Actual E-Skills
Actual performance
The purpose of this study was to do a comparison on the public’s perception of
their actual computing e-skills as to their actual abilities when performing
related tasks. Actual knowledge introduces the potential for a relationship
between perceived skill and openness to learn more and a potential discrepancy
between perceived and actual knowledge. The main factor identified by the
literature in relation to ‘‘computer literacy’’ is self-efficacy; the availability of
suitable computer training, that comprises of learning styles, past computer
related experiences; age; and gender. The literature on each individual is briefly
reviewed here as it is reasonable to suspect that individuals could influence
technological fluency either directly, or indirectly. Perception is an important
part of confidence (Messineo & DeOllos, 2005).
Procedures of internet use are the focus of many existing Internet skill
measurements (e.g. Bunz, Curry & Voon, 2007; Hargittai & Hsieh, 2012; Krueger,
2006; Potosky, 2007). A reasonably larger number of studies conducted self-
perception based surveys of students. Kwon and Song (2011) used a 10-item self-
perception information competency scale (based on the ACRL standards) at a
large public university in the southwestern United States. Kumar and Ochoa
(2011) used an online questionnaire through Survey Monkey to assess perceived
confidence in online searching of graduate students of at the University of
Florida.
“Hadimani and Rajgoli (2010) used a self- assessing questionnaire to investigate
Internet Literacy skills (mapped to the ALA standards) of undergraduate students
of a college of agriculture in India, other examples of self-perception surveys
are Ren (2000); Kurbanoglu (2003); Abate and Blommel (2007); Oliver (2008);
Perrin, Hossain, and Cumming (2008); Korobili, Malliari, and Christodoulou
(2009); Simpson-Scott (2009); Smith, Salaway, and Caruso (2009a, 2009b);
Sasikala and Dhanraju (2011); Hodgens, Sendall, and Evans (2012); and Pinto
(2012).”
!
Time
Hargittai (2006) measured e-skill observing whether people are able to complete
a task successfully given an unlimited amount of time to look for the material,
this had a both positive outcomes and limitations in the study. The positive
outcome was the applicants were more successful at the task given and the
limitation was the assessment took a longer period of time. It was time
consuming and therefor resulted in a smaller sample size (Hargittai & Shafer,
2006).
!21

!
Performance/Observation measures
Source Assessment detail Example task(s)
Hargittai (2002a) “Observation of 17 search tasks;
assessment based on completion
and time”
Some general tasks such as
finding information about a
politicians or the contact
information of a friend.
Others need more specific
content such as a recipe from
a website which clearly
states if it could be used for
someone who is lactose
intolerant (2002a: 1242).
Eshet-Alkalai and
Amichai-Hamburger
(2004)
5 computer-based tasks
measuring: photo-visual literacy;
reproduction literacy;
information literacy; branching
literacy; socio-emotional literacy.
Evaluated on performance
criteria (2004: 424).”
“The socio-emotional
literacy of participants was
examined by exposing them
to a chat-room situation…
Participants conducted ten-
minute chat sessions, in
groups of ten people each
time. Each participant was
identified by a false name
(real identity known to the
researchers only). The chat
topic was a hot political
issue that was in the news
headlines of the
month” (2004: 425)
Van Deursen and
Van Dijk (2009)
“9 tasks measuring operational,
formal, information, and
strategic skills
Performance measured on Task
assessment based on completion
and time”
“Perform a search on the
Postbus51 website with
keyword ‘rental price’.
Open the first search result.
Open the second search
result” (2009: 401).
!22

Factors influencing self-reported and actual e-skills
Significant variables that could relate to disparities of e-skills include gender,
age, and educational background. Seldom, men score higher on all e-skills tasks.
However, actual performance in most cases result in no gender differences
(Hargittai & Shafer, 2006; van Deursen & van Dijk, 2010).
Skill assessments in the past have revealed many relationships between e-skills
and other variables. Most often, researchers have measured internet skills as
the outcome of interest. Researchers have investigated the relationship of user’s
e-skills to their age, gender, and education background, as well as their
experiences using technology. The discussions below are the main findings
introduced along with the particulars of the study.
i. Gender
Academics have also considered gender being a variable which influences
internet skills. Although some studies have resulted in no significant relationship
between these two variables (Bunz, 2009), Hargiattai (2008) has found that
women have a tendency to rate their skills less than men, regardless of their
performance measured assessments , hence even so if gender may merely
indirectly affect internet skills, it could still possibly be a determining aspect in
an individual’s perception (Hargittai, 2008).
Current research additionally reveals that, the internet has been used for longer
durations by males (Durndell & Haag, 2002), also computer anxiety shows no
gender differences (Durndell & Haag, 2002; Schumacher & Morahan-Martin,
2001), part of the explanation is because of computers being used more in the
workplace. Thus computer anxiety will be ignored in this study.
Dodge et al. (2011) Interview protocol designed for
children Coding scheme: 1 for
“affirmative answers/
demonstrations of skill”; 0 for
“no/missing/or “I don’t
know”” (2011: 92)”
“Can you show me how to
get on the internet?”
“What if you want to find
information about
something you don’t know
about—what is one thing
you could do on the internet
to learn about something
you don’t know?” (2011:
90–91).
(Litt, 2013)
!23

ii. Age
Both positive and negative associations identified with empirical research which
studied the relationship between age and e-skills. In Hargittai (2002) 54
individuals aged 18–81 were observed, the study results implied that “younger
respondents were more likely to successfully and quickly complete a greater
number of information seeking tasks”. Bunz’s (2009) studied over 200 adults and
similarly identified that younger adults self-reported more fluent and less
anxious using computers, email, and the web than older adults. In another
study, children reported higher levels of internet competence than their parents
(Odendaal et al., 2006). Most people older than 50 years had no exposure to
computers in secondary school or college. Today, children begin using computers
for play and work, in schools and at home, at a very early age (Bradlow et al.
2002).
!
iii. Education
Education is a factor found to influence e-skills. There is a positive relationship
found between education and e-skills identified in Bradlow 2002 study. The
higher one’s education level the more likely a person is to possess greater
internet skills (Bradlow, 2002), with the importance that computers play in
everyday life, the societal norms for computer literacy have changed. As an
example, one of the requirements for graduation in many states have instituted
computer proficiency examinations, to ensure that all high school graduates
obtain basic computer mastery (Bradlow et al., 2002).
A study conducted by Hakkarainen et al. done a national investigation on
students in their elementary and high school years on skills and practices of
using new ICT. The results showed that computer supported learning makes
learning more meaningful and encourages more efforts to study. Self-reported
competence strongly correlated with the use of ICT at home and lastly the
intensity of ICT usage at school is determined more by availability of equipment
rather than students ICT skills (Hakkarainen et al., 2000).
!
iv. Technology experience and internet use.
Researchers have also found that how long individuals have been using a specific
medium of technology and internet experiences effect internet skill levels
(Harrison & Rainer Jr, 1992). The more individuals use the internet, the more
skilful they become is seen in evidence by Hargiattai (Hargittai, 2002b). Bradlow
and colleagues’ (2002) study of internet and computer proficiency found that
how long one had been using the internet and how much time one spent online
weekly was associated with higher internet skills.
!24

4. Observed E-Skills vs Self-Perceived E-Skills
Data collected from 100 adult internet users was used to matched users’ self-
perceived and performed internet abilities from Hargittai and Shafer (2006)
study. perceived skills is tested by, the researchers requested respondents to
evaluate their internet skills using a five- point scale from “not at all skilled” to
“expert”. Respondents were judged based on their observed completion of a set
of information- seeking tasks which evaluated their skills performance. The
results obtained confirmed that “while men and women did not vary in their
performance-based skills, women perceived their skills to be lower than men
did”. Another study by Barlow (2002) compared these two measurement types
found a “modest” correlation between users’ self-rated computer and internet-
related knowledge and a more objective multiple choice knowledge assessment.
Nevertheless, there were differences depending on the topic: Participants have
a tendency to overrate their knowledge of internet- related items, but
underrated their computer knowledge.  
!25

Studies Combing both Self-Perceived and Observed E-Skill Assessments
Source Assessment detail Example item(s)
B r a d l o w e t a l .
(2002)
Twenty-seven questions on
concepts like email and
information search; assesses
both objective multiple choice
items and self-rated knowledge
“The ability of email
a p p l i c a t i o n s t o
automatically respond to all
incoming messages with a
return message specified by
the recipient (e.g. ‘I am out
of town this week.’) is”.
Response items: “Currently
available”, “likely to be
available soon”, “not
t e c h n o l o g i c a l l y
feasible” (2002: 242)
Hargittai (2005,
2009)
Self-reported measures based on
familiarity to survey items; these
topics were selected based on it
the relationship to objective
measures of skill
“How familiar are you with
the following computer and
internet- related items?
Please choose a number
between 1 and 5, where 1
represents no understanding
and 5 represents full
understanding of the item”.
Hargittai and Shafer
(2006)
Performance measure: 8
information-seeking tasks
evaluated based on completion
and time. Self-reported
measure: Asked respondents to
judge their own skill using a
five-point scale
Example items: “Reload”,
“advanced search”,
“PDF” (Hargittai, 2009:
131).
Information tasks included
searching for information
like: “job or career
opportunities” and “a
museum’s or gallery’s
website” (2006: 438).
Self-reported response
items: “not at all skilled”,
“not very skilled”, “fairly
skilled”, “very skilled”,
“expert” (2006: 441).
!26

!
Gui and Argentin
(2011)
Multiple choice, performance
tasks, and open-ended questions
“Surfing on the website
www. barilla.it (the link is
active) find how many
minutes it takes to cook a
ribbed shells pasta
variety” (2011: 23)
(Litt, 2013)
!27

!
5. Conceptual Model
The above literature review resulted in the development of the study’s
conceptual model illustrating hypothesized relationships to be tested.
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The hypotheses derived are as follows:
5.1. Hypotheses:
• H1: Computer Self-efficacy levels have a positive relationship with
Performance Expectancy
• H2: Computer Self-efficacy levels have a negative relationship in regards
to time taken to complete the e-skills assessment
• H3: Computer Self-efficacy levels have a positive relationship with Actual
Performance
• H4: The greater Performance Expectancy of the task(s), the lower the
time taken to successfully complete the corresponding e-skills task(s)
• H5: Computer Self-efficacy levels have a positive relationship with Actual
Performance
!28
CSE
Performanc
e
Time
Actual
Performanc
Demographics
• Age
• Gender
• Education
• Prior
Computer
Experience
• Regular
Access
H1
H2
H3
H4
H5
H6H7
Figure 1 Conceptual Model

• H7: Those who completed on their own (Successfully Complete) took
significantly less time than those who required assistance (Partially
Completed)
!
In testing hypotheses 2, 3, 4, and 5 the question as to whether self-perceived e-
skills are useful predictors of actual e-skills has been answered. Computer self-
efficacy and Performance Expectancy are measures of self-perceptions of the
individual’s e-skills. Success rating based on completion and time taken to
complete the e-skills assessment task(s) determined actual performance
Hypotheses 2 and 4 investigates the relationship of these self-perception to time
taken to complete the e-skill assessment task(s) under pressure as a measure of
actual e-skills. If the correlation is weak, this will support the hypotheses of the
self-perceptions being a reliable indicator of the time factor of Actual
Performance. Hypotheses 3 and 5 investigates the relationship the respective
determinants of self-perceptions to the success ratings on the e-skills
assessment task(s) as a measure of Actual Performance. If the correlation is
strong and positive, this will support the hypotheses of self-perceptions being a
reliable indicator of the success of rating factor of Actual Performance.
Ultimately, these determine the relationship between self-perceived e-skills and
actual e-skills of library users.
!
!
!
!
!
!29

Chapter 3 – Research Methodology
3.1 Introduction
This chapter discusses the research paradigm and design, the population
targeted for the research, and the construction of the data collection
instrument being used. The analysis plan will then be discussed. The last
sections will include validity and reliability, assumptions, scope and limitations
of the research.
3.1.1 Research methodology / paradigm
The concept of ‘paradigms’ exists within social sciences research. These
paradigms are frames of references that direct the way people view and reason
surroundings. These belief systems structure out cognition in the way we
observe social reality and thus direct the approach in which the research will be
carried out (Bhattacherjee, 2012). Positivism and post-positivism are currently
the two popular paradigms that exist in social sciences. Positivism suggests that
knowledge creation can only be accomplished by researching phenomenon that
can be observed and measured, and research in this paradigm has therefore
relied heavily on theories which can be tested (Bhattacherjee, 2012).
Alternatively, post-positivism indicates that through the combination of
empirical observations and logical reasoning inferences can be drawn on
phenomena (Bhattacherjee, 2012).
In this study a positivist paradigm is to be used as the research will be
conducted where only what can be observed and measured will be considered,
otherwise known as empiricism which aims to imply that no attempt will be
made to reason beyond the observable facts. The positivist paradigm reflects
relatively close to the values of quantitative research methods such as survey
and experimental research, these methods will be discussed detailing the
rationale in more detail (Bhattacherjee, 2012).
The quantitative approach will additionally provide a distinct answer that will
be reached regarding the reliability of self-reported e-skills observed of the
sample. The research methodology gives a measurable answer which can then
be interpreted (Smith, 1983) – this is in line with the research question. Using
this method, a generalisation will be made to the specific libraries of study from
the collected data. The need exists to be objective in this method and focus on
the question on hand (Kamil, 2004). Furthermore, numbers and statistics play a
big role in interpreting the data (Kamil, 2004).
This method is appropriate for this research because of the following reasons: a
clear answer is required from the research, there needs to be complete
objectivity from the researcher as the answers of other people is what is being
investigated, and lastly the focus of this research is narrow having only one goal
and the data needs to be interpreted in such a way that there is measurable
results.
- ! -30

!
3.1.2 Research Design
With the positivist paradigm and quantitative methodology having been chosen
there are certain research designs that fit the goal of positivist/quantitative
studies to test theory/hypotheses (Bhattacherjee, 2012). These research
methods include experiments, field surveys, secondary data analysis and case
research (Bhattacherjee, 2012). This study will follow the field survey research
design, more specifically cross-sectional field surveys, at the same point in time
independent and dependent variables are measured by using a single
questionnaire. Field surveys capture certain perspectives from a random sample
of individuals in the field using a questionnaire (Bhattacherjee, 2012). The
benefit of such a research design is that it has strong external validity, therefore
increasing the generalizability of the results (Bhattacherjee, 2012). Survey
research is most appropriate for individual studies (Bhattacherjee, 2012). The
research aims to infer certain generalisations to a larger population; the unit of
analysis for the study is also the individual library user. Since survey research
has strong generalizability and is most appropriate for individual studies it
meets the required criteria to conclude that it is the most appropriate research
design for this study. Under this design, a standardized questionnaire was thus
used to obtain information from respondents about their demographics,
computer experience, computer self-efficacy, self-reported e-skills; thereafter
the researcher proceeded with an e-skills test which assessed elements of their
actual e-skills.
The context for this study is the libraries within the City of Johannesburg.
Commonly, dictionaries refer to a library as a collection of resources and various
media (The Oxford English Dictionary. 11th ed. 2008). Reitz (2005) defined the
‘virtual’ 21st century library as a “library without walls” in awareness that
collections do not solely exist in tangible forms such as paper and books, but are
electronically accessible in a digital format via computer networks (Reitz,
2005). It would then be reasonable to derive that users require technologies to
access and skill to effectively make use of library collections and external
sources of information such as the internet.
Nwalo (2003) characterizes a library user as anybody who exploits these
resources that are provided by the library in order to fulfil their information
need (Anyira, 2011). There are various reasons users need information. Anyira
(2011) identifies needs such as personal self-development which enables people
to enrich themselves and remain relevant; obtain health information; seeking
information for a solution to a problem to keep abreast regarding their chosen
profession such as better jobs or students who are in school need information to
do assignments or study for tests; in the context of this paper the user
essentials are relevant to the government people who need up to date
information regarding their government such as about policies and plans.
!
- ! -31

3.2 Population and sample
3.2.1 Population
The population describes the entire (collective) unit of analysis that has the
characteristics that you want to study (Bhattacherjee, 2012). In this study, the
population would describe all the individuals who make use of the libraries that
is located in the metropolitan borders of Johannesburg. The CoJ is one of three
municipalities in Gauteng, South Africa and consists of seven regions. Only
public libraries will participate in this research. This purposeful choice of
population is appropriate for reasons mentioned. These libraries are convenient
in the sense that it represents the public library users in comparison to all other
private library users.
!
Library users who are associated with city libraries will be used as subjects for
this research for three strong reasons. First, the library users were assumed to
have direct access to the ICT’s and are of most interest to the research at hand.
It is these residents who must determine, based on their level of e-skills,
whether the ICT upgrades are effectively being made use of. Should the results
of this research lead to a change of policy or training initiatives at city libraries,
it is these residents who will be affected the most.
Secondly, the libraries are also assumed to be used by a vast diversity of
residents being situated in the in different areas of the city. Therefore, based
on their personal backgrounds and demographics, users in these libraries would
exhibit sufficient variation on the study’s variables to facilitate testing of the
study’s conceptual model.
!
3.2.2 Sample and sampling method
i. Sampling frame:
The sampling frame is a list of accessible participants that meet your population
criteria (Bhattacherjee, 2012). This studies’ sampling frame will be users from a
list of 35 libraries that are part of the “Public Access to Internet Project –
Implementation 2014/15” which was supplied by CoJ personnel. At present,
computer and Wi-Fi accessibility is available at the Jabavu, Noordgesig, Orange
Farm, River Park, Diepsloot and Sandton libraries, with another 38 libraries to
be added by June 30 (Vijayakumar & Kannappanavar, 2012). This however did
not go according to plan. A comprehensive list of libraries which have, or in the
process of gaining the ICT upgrades was referred by Nombuto, the Director of
Johannesburg Library and Information Services. See list in Appendixes.
This sampling frame is not exclusively representative of all the users of the
library as a user may not be a member. This group may not be generalizable to
users of libraries in the region let alone to the Johannesburg library users at
large.
- ! -32

- ! -33
Table 1 Sampling Frame

i. Sampling Technique:
Regarding sampling techniques there are two categories namely probability
sampling and non-probability sampling. Probability sampling is when every unit
in the population has a chance of participating in the study and this chance can
be determined and is accurate (Bhattacherjee, 2012). The use of the non-
probability sampling technique on the other hand means that certain units of
the population have no chance of participating or the probability of this chance
cannot be determined (Bhattacherjee, 2012).
The choice of probability sampling is appropriate if the generalization of your
sample is an important factor in a study (Bhattacherjee, 2012). Since this study
wishes to infer generalisations it is therefore fair to conclude that the
probability sampling technique is the most appropriate choice for the proposed
study. Within probability sampling there are further techniques namely simple
random sampling, systematic sampling, stratified sampling, cluster sampling,
matched-pairs sampling and multistage sampling. The random sampling
technique has the most generalizability and is the easiest of the mentioned
techniques (Bhattacherjee, 2012). Due to good generalizability, it is again, an
appropriate technique for this proposed study.
The sampling list is divided into 3 groups. Group 1 is the “Pilot” phase and
consists of 5 Library Sites; Group 2 and Group 3 consisting of 15 Library Sites
each. From the list, there were vague misunderstandings about libraries 13, 15,
23, 26, and 35 thus were removed. The reasoning is as follows: Libraries 13 and
35 were replaced indicated by a different font colour, however the process or
reasoning is unclear. Library 15 is a children’s library which is beyond the scope
of this research. Libraries 23 and 26 had ‘no line of site’ which is ambiguous by
contextual definition.
Thereafter it was seen as unfeasible to conduct research on small libraries due
to expecting a low response rate. This reasoned the removal of libraries which
have less than 10 public work stations. This reduction left Group 1 remaining
with 5 library sites; Group 2 reduced to 12 library sites; and Group 3 reduced to
8 library sites. Then it was decided to divide the groups into smaller
proportions. The common whole number denominator is 4. Thus one library from
Group 1 (5/4) is to be selected; three library sites from Group 2 (11/4); and two
library sites from Group 3 (8/4). A total of six library sites are thus to be
selected. It was decided to randomly select library sites based on Region – the
rule is that a region can only be selected one time per group. It is interesting to
compare the data collected from these libraries with the main Johannesburg
City Library in which there is no public internet access thus far. Thus data will
be collected in a total of 7 libraries.
!
The result of the random selection is as follows:
- ! -34

Table 2 Random Selection Results
!
A random walk method was used for data collection (Rice & Hancock, 2005).
This method is relatively easy to adapt and is both quick and economical when
collecting data (Rice & Hancock, 2005). As there was no rule for selection,
every person who was encountered on the random walk was invited to
participate in the study and only those who accept the invitation will be part of
the sample. If participants were unsure of the topic, a light explanation was
given to clear up any concerns as well as a cover letter to introduce the study.
A minimum sample of 90 respondents was targeted. This takes into
consideration unusable responses and unoccupied libraries. Surveys were
handed out from 9am to 4pm during the data collection period with an hour of
lunch break from 12pm to 1pm.
Library Name Region P U B L I C
Workstations
Roll-out Plan
1. Diepsloot A 20 Group 1
Phase 1 – Pilot
Sites
2. Randburg B 24 Group 2
Phase 1 -
3. Sandton E 28 Group 2
Phase 1 -
4. Lenasia Ext. 1 G 14 Group 2
Phase 1 -
5. Klipspruit West D 14 Group 3
Phase 2
6. Southdale F 10 Group 3
Phase 2
7. Johannesburg
City Library
F 0 No Public Access
T o t a l
libraries
7 T o t a l
workstations
110
- ! -35

If the library sites did not have enough users on the day of data collection, the
researchers purposively changed location to the library site with the most
number of workstations in that group. For that purpose, the following
contingency list of library sites was constructed using the same random
selection sampling strategy as mentioned above.
Table 3 Contingency Library List
The Research Instrument
The study is completely voluntary and has three parts. A confidential survey was
administered to the respondent followed by a structured interview to assess the
actual e-skills of library users. The survey questions and computer test tasks
items were adapted from various academic sources that were discussed in the
previous chapter.
Library Name Region P U B L I C
Workstations
Roll-out Plan
1. River Park E 62 Group 1
Phase 1 – Pilot
Sites
2. Bosmont B 40 Group 2
Phase 1 -
3. Meadowlands D 37 Group 2
Phase 1 -
4. Sandton E 28 Group 2
Phase 1 -
5. Pimville D 20 Group 3
Phase 2
6. Glenanda F 18 Group 2
Phase 1 -
7. Johannesburg
City Library
F 0 No Group
T o t a l
libraries
7 T o t a l
workstations
205 Total responses
- ! -36

The questionnaire used was structured, meaning that the respondent had
options to choose from a set choice of answers (Bhattacherjee, 2012).
Structuring the questionnaire allows for aggregation in terms of a composite
scale or index and hence allow for statistical analysis - testing of hypotheses
(Bhattacherjee, 2012).
The level of measurement used in the questionnaire to operationalize the
constructs was the Likert scale. The Likert scale was chosen as it allows for a
more descriptive response than a binary scale and has therefore been a popular
choice in social science research (Bhattacherjee, 2012). These more descriptive
responses are achieved by adding more possible responses including the addition
of neutral rather than the traditional ‘Yes’ and ‘No’ binary responses which is
used in similar and previous studies e-skills assessments.
In the first stage a simple paper based questionnaire was answered, the
participants were asked to self-report their e-skills in the questionnaire. The
survey gathered broad demographic data, which included the number of years
using computers and technologies of which the user has regular access to. Then
a self-reported level of general computer self-efficacy was self-reported by the
participant.
Administration is described as the questionnaire collected the library user’s
demographic information, and level computer self-efficacy, both general and
specific Performance expectancy. This required the respondent to self-report
the performance they expected on the specific tasks as a predictive measure of
the e-skills assessment outcome. The results from the CSE survey and
performance expectations will provide insight on perceived e-skills.
Following, subjects were asked to rate their ability to perform e-skills in various
tasks, also referred to performance expectancy for specific tasks. The types of
tasks included: download a pdf; use e-mail; participate in a forum; identify
local news; and using a search engine, among others.
The objective e-skills assessment observed an individual’s competency regarding
completion of specific ICT related tasks as well as the time taken to complete
the specific task, which was recorded using a standard sports stop-watch. The
results of the observed e-skills assessment coupled with the time taken to
complete the assessment will provide indication of the individual’s actual e-
skills.
!
The table below consists of the sources of the items considered in the
questionnaire:
Table 4 Concept-Variable Table
Concept/Variable Measurement Operationalizatio
n
References
- ! -37

Computer self-
efficacy
• CSE scale Likert scale (1–10)
Questions:
I could complete
electronic tasks
using the libraries
computers and/or
internet…
1. If there was
no one
around to
tell me
what to do
as I go.
2. If I had
never used
a computer
like it
before.
3. If I had only
manuals for
reference.
4. If I had seen
someone
else using it
before
trying it
myself.
5. If I could
call
someone for
help if I got
stuck.
6. If someone
else had
helped me
get started.
7. If I had a lot
Compeau and
Higgins (1995);
Wei et al
(2011)
- ! -38

i. Pre-test
The pre-test was conducted by 6 Information System lecturers at University of
the Witwatersrand. Mainly grammar and layout suggestions were made, however
one lecturer suggested the inclusion of a question which captured if the
respondent has regular access to common technologies such as smartphones,
tablets and personal desktops. These have been implemented and resulted in
the final questionnaire (see Appendix B).
Performance
Expectancy
• Self-perceived
success on
completing a
specific task.
Likert scale (1–5)
Questions:
Rate your
capability to
perform the
following e-skills
tasks:
1. Locate website
using browser/
search engine.
2. Use email to
communicate.
3. Download PDF.
4. Upload file.
5. Participate in an
online discussion
forum.
6. Identify news.
Hargittai and
Shafer (2006)
Actual
Performance
• Time Seconds H a r g i t t a i
( 2 0 0 5 ) ;
H a r g i t t a i &
Shafer (2006);
H a r g i t t a i
(2008)
• Success of
task
completion
Not Completed –
P a r t i a l l y
C o m p l e t e d –
S u c c e s s f u l l y
Completed
- ! -39

4. Procedure for Data Collection
The data collection duration was over 9 days during August 2015. The library
sites were clustered in their respective groups for contingency purposes. The
table below describes the data collection period for this study, the use of the
primary and contingency libraries and the number of responses collected from
each.
!
Table 5 Data Collection
Date for
collecti
on
Randomly
Selected
Library
Regio
n
Sample
size
collect
ed
Contingenc
y Library
Regio
n
Sample
size
collect
ed
Roll-
out
Plan
Day 1 Diepsloot A 16 River Park E 0 Grou
p 1
Phase
1 –
Pilot
Sites
Day 2 Randburg B 5 Bosmont B 9 Grou
p 2
Phase
1 -
Day 3 Sandton E 19 N/A N/A N/A Grou
p 2
Phase
1 -
Day 4
and Day
5
Lenasia Ext.
1
G 25 Meadowlan
ds
D 0 Grou
p 2
Phase
1 -
- ! -40

i. Administration Protocol
Firstly, permission was requested from the library executives or contact persons
for their users to be allowed to participate in the study. The table below shows
the details for each library potentially part of the sample (see appendix A).
Research assistants were trained on the procedure to follow before data
collection activities preceded. All data collection days had on-site tablets for
residents’ use with internet connection to connect online for the assessment.
The internet connection was either from the smart city Wi-Fi provided by the
libraries or by the 3G connection provided by Vodacom service providers.
Researchers wore clothing in affiliation with the University of the
Witwatersrand, greeted library users’ and presented the study in a friendly
manner. The researchers informed the residents about the purpose and
procedure involved in the study verbally as well as with the cover letter (see
appendix B). There was also be an introductory paragraphs on sections of the
questionnaire (see appendix C), if elaboration was needed it was explained by
the researcher. If the subject agreed, the survey continued.
Following the completion of the questionnaire, participants completed a series
of hands-on tasks. Hereby, instructions were introduced to the respondent in
order to complete the assessment on the Samsung tablet (see Appendix D and
E). Their performance will provide a more objective measure of their e-skills.
The two dimensions of their task performance will be time to completion scored
in seconds, and performance scored as ‘Not Complete’, ’Partially Complete’,
‘Successfully Complete’. The tasks included instructions to interact with e-
governance related websites and other internet components as the tablet-based
e-skills test. The test contained numerous sections to assess subject knowledge
in specific applications. It was an observational performance evaluation by the
Day 6 Klipspruit
West
D 2 Pimville D 9 Grou
p 3
Phase
2
Day 7 Southdale F 5 Glenanda F 4 Grou
p 3
Phase
2
Day 8
and Day
9
Johannesbu
rg City
Library
F 20 - - - No
Grou
p
Total
libraries
7 Total
days
9 Max. Total
responses
116
- ! -41

researcher. The researcher recorded the time of how long subjects take to
accomplish a task with a standard sports stop-watch.
Research assistants were trained and briefed on how conduct the research
procedure correctly. The researchers followed the ‘Assessment Guidelines’ (See
Appendix E) to evaluate a participant’s performance.
Coding Scheme
The following coding scheme was used to measure the success of the actual
performance of the e-skills assessment.
For each task
A time limit of 2 minutes is identified as a normative cut-off value. Individuals
who could not complete the task within 2 minutes or who asked questions
before 2 minutes were marked as partially completed on the task.
In addition, individuals who asked questions after 3 minutes were marked as
partially completed,
Anyone who gave up or completed after 5 minutes was marked as not completed
Individuals who considered themselves as have completed but the task was not
actually correct were also marked as not completed.
!
!
!
 
- ! -42

5. Data Analysis and Interpretation
The tool that is to be used is the IBM SPSS Statistics program. Descriptive
statistics will be used to analyse data in order to define it in a meaningful way.
CSE and performance expectancy were multi-item scales. First a PCA was
carried out. Missing data was dealt with by deleting cases with researcher error
or more than ten percent of missing data. Thereafter, missing data will be
replaced using the mean of the observations. Outliers are expected in this study
thus will remain as valid observations.
Then scale reliability will be determined by Cronbach’s alpha only on the
Computer Self-Efficacy measure. Additionally, correlation between items with
low loading against other items will be prepared to further analyse if the item(s)
is to be dropped. Consequently, a composite score will be generated as this is a
multiscale item.
Descriptive statistics, such as frequency counts will be used to determine a
respondent profile for the demographics of the study. Thereafter correlation
analysis was used to establish the relationship between CSE, performance
expectancy, task completion and time was conducted to investigate the
hypotheses at hand
!
!
!43

!
6. Limitations
• The primary limitation of this study will be the minor sample size.
• The range of demographics the study has got responses from might not be a
true representative of city library users - as the data collection period is to
be during working hours, potentially alienating a big section of residents.
• Respondents’ responses may be influenced by external factors on that
particular day, not to what would benefit the city as a whole.
• Johannesburg, being quite large geographical area, and cannot be
generalised from the Implementation Plan 2014/2015 list.
7. Validity and Reliability
According to researchers, cognitive issues and situational issues are important
aspects to study the validity of self-report. Cognitive issues refer to the
respondents understanding of the content or they have sufficient knowledge to
correctly answer the questions. Situational issues address the impact of the
environment that the survey is conducted, in this case being the library. The
content of the survey may have been dishonest by providing socially desirable
responses, which may differ when coupled with the environment setting. It is
expected that in a library setting, users might exaggerate their e-skills where as
they might be more honest in corporate setting where colleagues may be able to
review their responses. It is evident in past research respondents have a fear of
reprisal which affects validity. This provides for common recommendation that
environment and administration of the survey is carefully planned and executed by
survey administrators. Precise results are more likely when a respondent has a high
impression of anonymity and little fear of reprisal.
7.1.External validity
External validity refers to the generalisability of the outcome from the research –
whether the outcome from the research can be widespread across for example,
the people at large (Calder et al., 1982). A threat faced by the research is the
misrepresentation of the population caused by sampling. To minimise the threat, a
random sampling method was used (Frerichs, 2008). The random sampling method
is intended to avoid biasness and will minimise, but not completely eradicate, the
risk.
!44

7.2.Internal validity
Internal validity tests the degree to which a study’s outcome can be interpreted as
being accurate (Casady, 2005). If any important items are omitted or outdated,
internal validity will face scrutiny. It is possible that certain factors may be
overlooked during the literature search. In order to establish a thorough list of
factors, literature will be extensively looked at.
To improve the validity, this research is to avoid the “bogus pipeline” technique,
whereby participants are informed that their responses will be validated by an
objective test after the survey (Brener & Grady, 2003). Due to participants
awareness of the testing it may influence more honest answers. Commonly, results
of the responses are then compared with participants who have not been informed
about the objective test. If the variance between responses of the survey and
objective test contrast significantly in the two situations then evidence will exist
to indicate if situational issues decrease validity of responses
(Center for Health and Safety Culture , 2011). Self-reports may not correlate with
actual performance due to the circumstances of the assessment and questionnaire
themselves.
!
Reliability
Reliability refers to the consistency produced in measuring something (Moskal &
Leydens, 2000). Cronbach’s Alpha, a means of internal consistency, is a solution to
testing the reliability of the research (Tavakol, 2011). The higher the value of
alpha on a scale of 0 – 1, the more reliable the study is (Tavakol, 2011). Reliability
may be threatened by the e-skills task items as there is no valid scale to measure
e-skills. Additionally, reliability is also threatened by the honesty of which
respondents answer. A main source of error within a test is attributable to the
sampling of items, because each person has the same chance of answering an item
correctly, the higher the number of items on the test, the lower the amount of
error in the test (Drost, 2004).
8. Ethics
Ethical considerations are significant due to the legal and social implications
research could have on respondents or organizations. Therefore the following
ethical concerns are at hand:
• This survey is completely voluntary and respondents may withdraw at any
stage.
• Respondent’s anonymity will be maintained and their identities protected –
The only identifying information is the ‘Participant Number’. This consists of
the day of the month/ researcher number / incremental number e.g. The
Seventh respondent on 18 August by the research assistant will have the
following Participant number: 18/2/7.
!45

• Research participants will be fully knowledgeable about the research
process and purposes, and must give consent for participation in the
research.
• All information obtained in this survey is confidential and will be used for
research purposes only – The survey results will be archived by the
University.
• This research was directed in agreement with the ethical and expert
guidelines of the Information Systems department at the University of the
Witwatersrand.
!
9. Research planning
Table 6: Time-plan for completion of research report
!
Chapter 4
!
Deliverable Due Date
Draft research proposal 16th
Research Proposal 15th
Chapter 1 29th
Chapter 2 22nd June
Ethics Application Due 23rd July
Chapter 3 & Questionnaire Draft 7th
Aug
Final Questionnaire 12th
Data Collection 17th
Chapter 4 18th
Chapter 5 2nd October
Chapter 6 9th
October
Final Report Due 23rd October
!46

Descriptive Statistics
Data Screening, Missing Values and Outliers
The data were collected through written questionnaires from a total of 10 libraries
in Johannesburg. Libraries in the sample represent six of seven regions within CoJ
borders. The selection of a diverse set of libraries in six different regions improves
for generalizability of the research findings to the broader sample frame of the
2014/2015 Implementation Plan. Altogether, 116 responses were received. All
responses received were from respondents who met the inclusion criteria. The
responses were screened to identify any data entry errors, any cases or variables
with large amounts of missing data, as well as univariate outliers. Of these 116
responses, nine cases were dropped from the study. All of these cases were
deleted as they were missing close to 10% of the data values. Thus the 107 useable
responses remained with enough complete data for meaningful statistical analysis.
The remaining data was then screened for univariate outliers. A good method of
detecting potential univariate outliers involves the examination of cases on each
questionnaire item where the standardized score is greater than ±3. This enables
the identification of cases with unusually high or low values on an item compared
to other cases in the sample. A review on standardized scores revealed that ‘time’
items had potential outliers, which was expected. None of the other cases
produced impressionable outliers. Four of the cases were missing one or more
observations and none were missing more than three (see Table 2). An examination
of the data did not reveal any underlying pattern.  
These few Missing values were therefore recorded using mean substitution.
Table 1 Number of cases with missing values
!
!
!
No. of missing values in a
case
No. of cases with
missing
1 2
2 1
3 1
!47

Respondent Profile
The final sample consisted of 107 useable observations. A Cross tabulation of
region and roll-out plan of useable responses is as follows:
!
Table 2 Cross tabulation: Region * Roll=out Plan
!
!
The intended proportion from the sampling strategy where Group 1 = 1 part, Group
2 = 3 parts, Group 3 = 2 parts, and No Group = 1 part compared to the obtained
proportion where Group 1 = 1 part, Group 2 = 3.4 parts, Group 3 = 1 part and No
Group = 1.2 parts. This indicates a shortfall of 15 responses from Group 3, as well
as a high representation of Group 2 representing about half the sample (See Figure
1 below).
!
!
!
Roll-out Plan
TotalGroup 1 Group 2 Group 3 No Group
Region A Number of Respondents 16 0 0 0 16
% of Total 15.0% 0.0% 0.0% 0.0% 15.0%
B Number of Respondents 0 13 0 0 13
% of Total 0.0% 12.1% 0.0% 0.0% 12.1%
D Number of Respondents 0 0 11 0 11
% of Total 0.0% 0.0% 10.3% 0.0% 10.3%
E Number of Respondents 0 17 0 0 17
% of Total 0.0% 15.9% 0.0% 0.0% 15.9%
F Number of Respondents 0 4 5 20 29
% of Total 0.0% 3.7% 4.7% 18.7% 27.1%
G Number of Respondents 0 20 1 0 21
% of Total 0.0% 18.7% 0.9% 0.0% 19.6%
Total Count 16 54 17 20 107
% of Total Roll-out Plan 15.0% 50.5% 15.9% 18.7% 100.0%
Note: Group 1 = Phase 1: Pilot Sites; Group 2 = Phase 1 ; Group 3 = Phase 2; No Group = No
implementation
!48

!
Figure
1
Frequency Chart: Group
Moreover there were no initial expectations for proportions of Regions the sample
derived from. The range between Region D represents about 10% of the sample and
Region F represents almost a third of the sample (See Figure 2 below).
!
!
Figure 2 Frequency Chart: Region
!49
Frequency Percentage Chart: Group
0
15
30
45
60
Group 1 Group 2 Group 3 No Group
Expected Actual

!
!
The genders of the respondents were spread out about evenly between males and
females throughout the study, with a slightly higher portion of males.
!
!
Table 3 Frequency Table: Gender
!
!
!
In regards to age and education levels. The chart below displays a cluster of young
respondents, as well as majority of the sample achieved matric or a post matric
education level. This could be explained by the time of year for the data collection
period. Many respondents were studying in the libraries and not visiting due to
leisure purposes.
!
Frequency Percent
Male 58 54.2
Female 47 43.9
Prefer not to say 2 1.9
Total 107 100.0
!50

!
Figure 3 Frequency Bar Chart: Education * Age Group
!
In regards to regular access to technologies, the majority of the sample have
access to cell phones/ smartphones. However, majority of the sample do not have
access to tablets. Personal computers are indicated to be available to under half of
the sample. This reflects that the sample consists of people who often do not have
access to technologies as most libraries were in underprivileged communities.
!
Table 4 Frequency table: Regular Access to Technologies
Cell phone/smartphone Tablet Personal Computer
Frequency Percent Frequency Percent Frequency Percent
Yes 89 83.2 29 27.1 50 46.7
!51

!
Computer experience indicates how long a respondent has been using computers. A
cumulative percent 43% indicates sample have three years’ experience or less,
while a cumulative percent of 57% provides an indication that the sample have
four years’ experience or more.
!
Table 5 Frequency: Computer Experience in years
!
!
Reliability and Validity
The specification of which resources (variables) belong to which resource
constructs reflects theoretical analysis and reasoning. Therefore, a series of test
were conducted to explore the reliability and validity of the computer self-efficacy
construct. The scale consisted of 10 items which measured the strength of an
individual’s judgment of their capability to use a computer.
To test the reliability of the constructs, reliability analysis was conducted using
SPSS. To assess the validity of the CSE construct, principle components analysis
with VARIMAX rotation, also using SPSS, was conducted. In this study, Barlett’s test
of sphericity (p=0.00) indicates that statistical probability that the correlation
matrix has significant correlations among at least some of the variables, and the
No 18 16.8 78 72.9 57 53.3
Frequen
cy
Perce
nt
None
8 7.5
Less than 1
year 17 15.9
2 - 3 years
21 19.6
4 - 5 years
16 15.0
6 years or
more 45 42.1
Total 107 100.0
!52

Kaiser-Meyer-Olkin measure of sampling adequacy (0.817) showed meritorious
sampling adequacy. The communalities presented in Table 6 below are all above
0.300.
!
Table 6 Communalities of Computer Self-Efficacy
Table 7 displays the reliability and factor analysis results. The result shows that the
CSE construct is a distinct un-dimensional scale which was extracted
Table 7 Component Matrix
Initial
Extractio
n
CSE_1 1.000 .740
CSE_2 1.000 .527
CSE_3 1.000 .419
(CSE_4) 1.000 .377
(CSE_5) 1.000 .581
(CSE_6) 1.000 .722
CSE_7 1.000 .529
CSE_8 1.000 .478
(CSE_9) 1.000 .764
(CSE_10) 1.000 .479
Extraction Method: Principal
Component Analysis.
Component
1
CSE_1 .555
CSE_2 .347
CSE_3 .610
CSE_4 .629
CSE_5 .727
CSE_6 .736
CSE_7 .744
CSE_8 .656
CSE_9 .779
CSE_10 .694
!53

!
Only item 2 has a Corrected Item – Total Correlation below 0.400 and therefore
dropped. The item means thereafter is 6.696 on the 11 point Likert-type scale.
Cronbach’s Alpha initial read at 0.843 but increased to 0.851 after item 2 was
deleted is. This is above 0.700 and therefore good evidence of reliability.
!
A composite score for CSE was therefore calculated as the average of the
remaining 9 items weighted equally.
Computer Experience, CSE and Performance Expectancy data was then tested for
normality. For all the variables, both the Kolmogrov-Smirnov and Shapiro-Wilk test
resulted in statistically significant different from a normal distribution (p<.01).
Therefore the null hypothesis of the normal distribution was rejected. In
conclusion that there is probably a non-normal distribution. Consequently, it was
decided to use non-parametric Spearman correlations to examine the relationships
between CSE, performance expectancies and actual performance on each of the e-
skill tasks.
!
Table 8 and 9 presents a high level overview of Actual Performance. For each task,
actual performance in terms of time (in seconds) was distributed on average for
each of the e-skills assessment tasks as illustrated in the Table 8 below.
Extraction Method:
Principal Component
Analysis.
a. 1 components
extracted.
Item-Total Statistics
Scale Mean if
Item Deleted
Scale
Variance if
Item Deleted
Corrected
Item-Total
Correlation
Squared
Multiple
Correlation
Cronbach's
Alpha if Item
Deleted
CSE_1 58.16 294.030 .497 .440 .832
CSE_2 60.26 312.616 .306 .219 .851
CSE_3 58.20 290.134 .515 .350 .831
CSE_4 58.05 300.186 .506 .304 .831
CSE_5 58.08 287.156 .599 .574 .822
CSE_6 57.83 287.456 .610 .585 .822
CSE_7 57.18 295.570 .617 .414 .822
CSE_8 58.02 286.315 .567 .365 .826
CSE_9 57.07 286.764 .636 .633 .819
CSE_10 56.70 296.227 .582 .516 .825
!54

Table 8 Distribution of Actual Performance in terms of Avg. Time
!
Actual performance measured as success on completion of e-skills assessment
tasks. Frequencies are as follows for each of the tasks (see Table 9).
!
!
!
Table 9 Summary of Descriptive of Actual Performance
N = 107 Avg. Time: Not
successful
Avg. Time:
Partially
Successful
Avg. Time:
Successfully
Completed
Avg. time for
task
Task 1 184.49 84.65 45.70 58.85
Task 2 67.23 45.70 45.70 84.64
Task 3 67.23 94.70 83.21 44.63
Task 4 11.51 65.50 42.68 73.17
Task 5 27.93 84.71 73.36 152.65
Task 6 19.99 158.67 160.44 71.19
N = 107 Not successful Partially Successful Successfully Completed
Task 1 6
(5.6%)
15
(14.2%)
86
(80.4%)
Task 2 12
(11.2%)
20
(18.7%)
75
(49.1%)
Task 3 28
(26.2%)
22
(20.6%)
56
(52.3%)
Task 4 18
(16.8%)
28
(26.2%)
60
(56.1%)
Task 5 23
(21.5%)
29
(27.1%)
55
(51.4%)
!55

!
Hypotheses Testing
!
A summary of the hypotheses testing results are presented below for H1, H2, H3,
H4, H5 and H7 (see hypotheses summary below). Total Time was composed by
aggregating the time taken on each task. Composite Performance Expectancy and
Actual Performance was calculated as the average of the 6 items weighted equally.
!
Task 6 12
(11.2%)
13
(12.1%)
81
(75.10%)
Total 99
(15.49%)
127
(19.88%)
413
(64.63%)
!56

Mean Performance Expectancy
(std. dev )
H1: Performance Expectancy Correlation with CSE
!!!Correlation Coefficient
Sig. (2-tailed)
(r =1) H2: Time Correlation with CSE
!
!
!Correlation Coefficient
Sig. (2-tailed)
(r=1) H3: Actual Performance Correlation with CSE
!!!Correlation Coefficient
Sig. (2-tailed)
(r=1) H4: Time Correlation with Performance Expectancy
(successfully completed only)
Correlation Coefficient
Sig. (2-tailed)
(r=1) H5: Performance Expectancy Correlation with Actual Performance
!Correlation Coefficient
Sig. (2-tailed)
(r=1) Actual Performance time in seconds
(successfully completed)
!Mean
(std. dev)
Task 1
Locate Website 3.99
(1.153)
N = 107.357**
.000
N = 107-.254**
.008
N = 107.199*
.040
N = 107-.298**
.005
N = 86 .238*
.014
N = 10745.7
(24.41)
N = 86
Task 2
!57

H1: The greater the Computer Self-efficacy levels of the individual, the greater
their Performance Expectancy
Spearman correlation was used to examine the correlation between the CSE
levels of library users (M=6.70, SD=1.97) and Performance Expectancy (M=3.97,
SD= 0.91). The correlation between the variables was found to be statistically
significant (r = 0.360, p<0.01). This finding provides support for hypothesis 1
that CSE of library users and Performance Expectancy are positively and
significantly related. A scatter plot (Fig. 3) illustrates the relationship.
This is also supported by the correlations between CSE and the Performance
Expectancies on the individual tasks. Correlations between CSE and Performance
Expectancy for Tasks 1, 2 and 6 was found to be statistically significant at α
levels of 0.000 (p<0.01); Tasks 4 and 5 was also found to be statistically
significant (p < 0.05). However Task 3 was not found to be statistically
significant at an α level of 0.055.
Figure 4 Scatter plot of relationship between Computer Self-
Efficacy and Performance Expectancy
!58

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